dor_id: 45578

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336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/366/363

100.1.#.a: Aguilar Torres, G.; Sánchez Pérez, G.; Toscano Medina, K.; Pérez Meana, H.

524.#.#.a: Aguilar Torres, G., et al. (2012). Fingerprint Recognition Using Local Features and Hu Moments. Journal of Applied Research and Technology; Vol. 10 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/45578

245.1.0.a: Fingerprint Recognition Using Local Features and Hu Moments

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2012

264.#.1.c: 2012-10-01

653.#.#.a: AFIS; FFT; Gabor filters; Hu invariant moments; minutiae; recognition

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/366

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041.#.7.h: eng

520.3.#.a: Person identification systems based on fingerprint patterns called Automatic Fingerprint Identification Systems, AFIS,are some of the most widely used biometric methods since they provide a high degree of success. The accuracy ofAFIS is mainly due to some unique characteristics called minutiae, which are points where a curve track finishes,intersects with another curve track, or branches off. During past decades several efficient minutia-based fingerprintrecognition algorithms have been proposed which achieve false recognition rates close to 1%, however, theirrecognition rate may be still improved. To this end, this paper presents a fingerprint recognition method using acombination of the Fast Fourier Transform (FFT) with Gabor filters for image enhancement. Next, fingerprintrecognition is carried out using a novel recognition stage based on Local Features and Hu invariant moments forverification.

773.1.#.t: Journal of Applied Research and Technology; Vol. 10 Núm. 5

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.22201/icat.16656423.2012.10.5.366

harvesting_date: 2023-11-08 13:10:00.0

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last_modified: 2024-03-19 14:00:00

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Artículo

Fingerprint Recognition Using Local Features and Hu Moments

Aguilar Torres, G.; Sánchez Pérez, G.; Toscano Medina, K.; Pérez Meana, H.

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Aguilar Torres, G., et al. (2012). Fingerprint Recognition Using Local Features and Hu Moments. Journal of Applied Research and Technology; Vol. 10 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/45578

Descripción del recurso

Autor(es)
Aguilar Torres, G.; Sánchez Pérez, G.; Toscano Medina, K.; Pérez Meana, H.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Fingerprint Recognition Using Local Features and Hu Moments
Fecha
2012-10-01
Resumen
Person identification systems based on fingerprint patterns called Automatic Fingerprint Identification Systems, AFIS,are some of the most widely used biometric methods since they provide a high degree of success. The accuracy ofAFIS is mainly due to some unique characteristics called minutiae, which are points where a curve track finishes,intersects with another curve track, or branches off. During past decades several efficient minutia-based fingerprintrecognition algorithms have been proposed which achieve false recognition rates close to 1%, however, theirrecognition rate may be still improved. To this end, this paper presents a fingerprint recognition method using acombination of the Fast Fourier Transform (FFT) with Gabor filters for image enhancement. Next, fingerprintrecognition is carried out using a novel recognition stage based on Local Features and Hu invariant moments forverification.
Tema
AFIS; FFT; Gabor filters; Hu invariant moments; minutiae; recognition
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces